Retail Credit Risk Modeling Leader (Credit Risk Administration)

US Bank; Minneapolis (MN); On-site; USD 180,000 - 240,000; Full time

Job summary

U.S. Bank is seeking a senior quantitative leader to oversee retail credit risk modeling within the Model Development and Decision Science (MDDS) group. The role covers CCAR and CECL, and requires shaping modeling strategy and representation in regulatory reviews.

You will lead the Residential Real Estate and Other Retail credit modeling teams, setting standards and partnering with business, risk, validation, and audit to drive high-impact risk decisions.

Qualifications

• Bachelor's degree in a quantitative field; nine+ years of relevant experience.
• Five+ years of experience leading credit risk model development.
• Strong knowledge of regression, time-series, and ML methods; model governance.
• Proficient in Python, SQL, SAS and data platform best practices.

Responsibilities

• Lead a portfolio of complex, high-profile retail credit model development projects.
• Set quantitative direction, model structures, and methodology standards across retail credit risk.
• Oversee model development, testing, documentation, implementation, monitoring, and use.
• Lead and develop managers responsible for retail credit risk modeling teams.
• Advance scalable processes, analytics capabilities, and data/tech support.
• Lead modeling responses to regulatory exams, audits, and validations; engage with regulators.

Skills

Quantitative leadership

People leadership

Communication

Statistical modeling

Python

SQL

SAS

Model governance

Regulatory knowledge

Education

Bachelor's degree in quantitative field

MA/MS/PhD preferred

Tools

Python

SQL

SAS

Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

The Credit Risk Administration (CRA) team at U.S. Bank is seeking a senior quantitative leader to oversee retail credit risk modeling within the Model Development and Decision Science (MDDS) group.

About the CRA Team

We are a highly dynamic and talented team which delivers on our mission through four pillars: Customer, Process, Talent, and Data.

• Vision | We create the future of credit risk management through data, analytics, and risk process innovation for our customers.
• Mission | We deliver data-driven information solutions to protect our stakeholders and inform the most significant financial decisions in the bank.
• Values | In addition to U.S. Bank core values, we prioritize collaboration, integrity, simplicity, and continuous learning.

About the Role

In this role, you will lead the Residential Real Estate and Other Retail credit risk modeling teams, including managers responsible for teams that build and maintain complex, high-profile models supporting capital stress testing, including CCAR, and allowance for credit losses, including CECL. Working with senior and executive leaders, you will shape retail credit modeling strategy and represent the domain in regulatory, audit, and validation reviews.

Key Responsibilities

• Lead a portfolio of complex, high-profile retail credit model development projects.
• Set quantitative direction, model structures, and methodology standards across retail credit risk, in coordination with other MDDS leaders.
• Oversee model development, testing, documentation, implementation, monitoring, and use to ensure consistent, high-quality practices.
• Lead and develop managers responsible for retail credit risk modeling teams, strengthening talent, succession readiness, and execution across the organization.
• Advance scalable processes, analytical capabilities, and supporting data and technology.
• Lead the modeling response to regulatory exams, audits, and model validations, and engage directly with regulators and senior stakeholders.
• Partner with and build strategic relationships with business, risk, validation, and audit leaders to align on high-impact issues.
• Communicate model approaches, results, limitations, and implications to senior and executive audiences to inform material business and risk decisions.

Basic Qualifications

• Bachelor's degree (MA/MS/PhD in a quantitative field strongly preferred) and nine or more years of relevant experience
• Five or more years of experience leading credit risk model development or closely related experience

Preferred Skills/Experience

• Quantitative leadership: Technical vision and credibility to shape modeling direction and standards across multiple teams and portfolios, with sound independent judgment in complex, ambiguous, and high-impact situations.
• People and change leadership: Demonstrated ability to develop managers and talent, build high-performing teams, establish succession readiness, and guide organizations through change.
• Communication and influence: Ability to explain complex quantitative concepts, approaches, results, limitations, and business implications clearly to senior, executive, and nontechnical audiences, while building trust and alignment with business, risk, validation, and audit partners.
• Statistical modeling and validation: Extensive knowledge of regression techniques, parametric and non-parametric algorithms, time-series, survival, segmentation, and other statistical methods, as well as model validation tests and methodologies. Experience with machine learning and explainability techniques is an added capability.
• Programming and data platforms: Experience using Python, SQL, SAS, or comparable analytical tools and modern data platforms to oversee, evaluate, and credibly challenge complex modeling work. Knowledge of sound engineering practices, including version control, testing, and reproducible pipelines, is preferred.
• Retail credit product and risk knowledge: Deep understanding of mortgage, home equity, credit cards, and other consumer lending products; borrower, collateral, and macroeconomic risk drivers; and quantitative and qualitative credit risk factors, portfolio risk, industry and competitive risks, and related risk-management approaches.
• Regulatory and model governance: Thorough knowledge of CECL, CCAR/DFAST, related supervisory guidance, model risk management, and emerging AI/ML governance expectations.
• Modernization and transformation: Experience leading platfor